Speed signal variance detection fault system and method

ABSTRACT

A method and a system is provided, useable in electrical control sensors for shaft speed signal frequency change rate tests, detecting intermittent or “in-range” failures. The method estimates a short-term variance (standard deviation) of the measured signal or signal rate of change, using the equation: Var[x]=E[x 2 ]−E 2 [x], where E[x 2 ] is an estimated average of the squared measured signal or rate of change over the short term, and E 2 [x] is a squared estimated average of the measured signal or rate of change over the short term. The estimated variance is compared with a predefined variance limit for a predefined amount of time, and if the estimated variance exceeds the predefined variance limit for the predefined amount of time, the measured signal is deemed invalid. A latching counter is used for timing, and its time out rate is preferably proportional to the time period the measured input is true. The step for estimating a short-term variance of the measured signal uses several filters performing averaging function.

BACKGROUND OF THE INVENTION

The present invention generally relates to turbine engines and, moreparticularly, to a method and system used in electrical control sensorsfor shaft speed signal frequency change rate tests.

Compressor and load shaft speeds are the primary control parameters ofgas turbine engines. Accurate speed measurement is essential for properengine control. In modern engines with electronic control systems, shaftspeeds are typically measured using passive variable reluctance magneticspeed sensors, which sense passing of gear teeth or similar objects. Thesensors output an electrical signal to the gas turbine electroniccontrol unit (ECU), with signal frequency proportional to the shaftspeed (i.e., passing speed of the gear teeth). The ECU measures thespeed by measuring the frequency of the speed pickup signal. The ECUtypically conducts reasonableness tests to insure the accuracy of thesignal before using it. These may include sensor impedance tests (tocheck whether the electrical characteristics of the sensor appearnormal), and signal frequency range and change rate tests (to checkwhether the resulting signal characteristics appear normal, within theexpected range and not changing at an unreasonable rate).

The conventional signal frequency change rate tests used to detectintermittent or “in-range” failures are unreliable because they eitheroften detect failures that do not truly exist (false alarms) or, inorder to avoid generation of false alarms, they miss real failureevents. There are four typical failure modes that need to be addressedby signal frequency change rate type tests. First failure mode includesintermittent electrical sensor failures that cause a noisy signal. Theother three failure modes include “in-range” failures. Second failuremode includes internal sensor failures which can cause “multiplecrossings” or cases where higher than normal speeds are readoccasionally. Third failure mode includes damaged gear teeth, shaftrunout or excessive speed pickup installation gaps, and can cause“missed teeth” and resultant speed measurement errors. Some conventionalcontrollers even have added sophisticated hardware circuits to detect“missing teeth”. On turbofans, the fourth failure mode is a catastrophicengine failure event called a “blade out”, which causes the controllerto perceive speed incorrectly and fuel the engine up.

As can be seen, there is a need for a method and system for implementingsignal frequency change rate tests, useable for detection of fourintermittent or “in-range” failure modes discussed above, which is morereliable and less complex.

SUMMARY OF THE INVENTION

In one aspect of the present invention, a system useable in electricalcontrol sensors for shaft speed signal frequency change rate tests,detects intermittent or “in-range” failures. It has means for measuringfrequency of a shaft speed signal; means for estimating a short-termvariance of the measured signal using the equation:Var[x]=E[x²]−E²E²[x], where E[x²] is an estimated average of the squaredmeasured signal over a short time interval, and E²[x] is a squaredestimated average of the measured signal over a short time interval;means for comparing the estimated short term variance with a predefinedvariance limit for a predefined amount of time; and means for deemingthe measured signal invalid, if the estimated variance exceeds thepredefined variance limit for the predefined amount of time.

In another aspect of the present invention, a system useable inelectrical control sensors for shaft speed signal frequency change ratetests, detecting intermittent or “in-range” failures, has means formeasuring frequency of a shaft speed signal; means for calculating arate of change (time derivative) of the measured signal; means forestimating a short-term variance of the measured signal rate of changeusing the equation: Var[x]=E[x²]−E²[x], where E[x²] is an estimatedaverage of the measured signal squared rate of change over a short timeinterval, and E²[x] is a squared estimated average of the measuredsignal rate of change over a short time interval; means for comparingthe estimated short term variance with a predefined variance limit for apredefined amount of time; and means for deeming the measured signalinvalid, if the estimated variance exceeds the predefined variance limitfor the predefined amount of time.

In a further aspect of the present invention, a method useable inelectrical control sensors for shaft speed signal frequency change ratetests, detecting intermittent or “in-range” failures, has the steps: (a)measuring frequency of a shaft speed signal; (b) estimating a short-termvariance of the measured signal using the equation: Var[x]=E[x²]−E²[x],where E[x²] is an estimated average of the squared measured signal overa short time interval, and E²[x] is a squared estimated average of themeasured signal over a short time interval; (c) comparing the estimatedshort term variance with a predefined variance limit for a predefinedamount of time; and (d) if the estimated variance exceeds the predefinedvariance limit for the predefined amount of time, deeming the measuredsignal invalid.

In yet another aspect of the present invention a method useable inelectrical control sensors for shaft speed signal frequency change ratetests, detecting intermittent or “in-range” failures, has the steps: (a)measuring frequency of a shaft speed signal; (b) calculating a rate ofchange (time derivative) of the measured signal; (c) estimating ashort-term variance of the measured signal rate of change using theequation: Var[x]=E[x²]−E²[x], where E[x²] is an estimated average of themeasured signal squared rate of change over a predefined short term, andE²[x] is a squared estimated average of the measured signal rate ofchange over the predefined short term; (d) comparing the estimatedvariance with a predefined variance limit for a predefined amount oftime; and (e) if the estimated variance exceeds the predefined variancelimit for the predetermined amount of time, deeming the measured signalinvalid.

These and other features, aspects and advantages of the presentinvention will become better understood with reference to the followingdrawings, description and claims.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 depicts a top level flowchart of a method for estimation of theshort-term variance of a signal, according to a preferred embodiment ofthe present invention.

FIG. 2 depicts a block diagram of a signal variance detection logic usedfor estimation of the short-term variance of a signal according to apreferred embodiment of the present invention.

FIG. 3 depicts a flowchart of a method for estimation of the short-termvariance of a signal rate of change according to a preferred embodimentof the present invention.

FIG. 4 depicts a block diagram of a signal variance detection logic usedfor estimation of the short-term variance of a signal rate of changeaccording to a preferred embodiment of the present invention.

FIG. 5 depicts a functional graph of the latching counter according to apreferred embodiment of the present invention.

DETAILED DESCRIPTION OF THE INVENTION

The following detailed description is of the best currently contemplatedmodes of carrying out the invention. The description is not to be takenin a limiting sense, but is made merely for the purpose of illustratingthe general principles of the invention, since the scope of theinvention is best defined by the appended claims.

The present invention includes a speed signal variance detection faultlogic system and method, available for signal frequency change ratetests, used to detect intermittent or “in-range” failures. It is morereliable than reasonableness rate tests, due to better failure detectionwith fewer false alarms. Moreover, it is less complex because it avoidsthe use of complex missing tooth detectors.

Although developed for compressor and load shaft speed parameters of gasturbine engines, the method and system of the present invention can beapplied for testing other sensed signals, such as exhaust gastemperature (EGT) probes signals, presently using other signal changerate tests.

The preferred methods of the present invention either calculate anestimate of the variance of the tested signal, or calculate an estimateof the variance of the rate of change of the tested signal. Due tooversampling, valid engine signals or signals rate of change do notchange much and the change is smooth. Thus, they show a highautocorrellation and small variance over the short term. Erraticsignals, such as signals corrupted by electrical noise, show rapidchanges during certain failures, the signal becomes much lesscorrellated and thus the variance increases. For the four speed signalfailure modes discussed above, the speed signal becomes much lesscorrellated and the variance of the signal or signal rate of changeincreases dramatically, allowing detection by a simple algorithm.

Variance of a signal x is defined by the equation:

Variance[x]=E [x²]−E²[x]

where E is an expectation operation used to estimate average of a signalx.

One method embodiment of the present invention estimates the short-termvariance of a signal using the following algorithm:

Variance[signal]=Filtered [(signal) ²]−(Filtered [signal])²

In this algorithm the approximate value of the expectation operation(E), which is the estimated short term average a signal x, is obtainedby an averaging filter.

FIG. 1 illustrates a top level flowchart of this method embodiment ofthe present invention, for estimation of the short-term variance of asignal. In step 100, the tested input signal is squared. In step 110, anestimate average of the squared input signal is obtained via filtering,generating an estimate of the average of x² over the short term. In step120, an estimate average of the input signal is obtained via filtering.It is then squared, generating a squared estimate of the average of xover the short term, for use in step 130. In step 130, an estimate ofthe short term variance is calculated, using the equation for variance:Var[x]=E[x²]−E²[x], where E is the expectation operator, or average. Instep 140, the estimated variance value is compared with a predefinedvariance limit and latching counter of the rate test. In step 150, it istested whether the estimated variance exceeds the predefined limit for agiven amount of time. If not, the test is over in step 160. If theestimated variance exceeds the predefined limit for a given amount oftime, in step 170, the signal is deemed to be inaccurate and invalidbecause the variance is too high to be that of a real signal.

FIG. 2 illustrates a block diagram of a signal variance detection logicwhich implements the method embodiment of the present invention, usedfor estimation of the short-term variance of a signal. In a multiplier200, the tested input signal is squared. In element 210, an estimateaverage of the squared input signal is obtained via filtering. Inelement 220, an estimate average of the input signal is obtained viafiltering. In multiplier 225, this signal is squared. In element 230, anestimate variance is calculated by subtraction of the two estimatedsignals obtained from elements 210 and 225. In element 240, thecalculated estimated variance value is compared with a predefinedvariance limit of the rate test. In latching counter (timer) 250, it istested whether the estimated variance exceeds the predefined variancelimit for a predefined amount of time. If the estimated variance exceedsthe predefined limit for a given amount of time, the signal is deemed tobe inaccurate and invalid because the variance is too high to be that ofa real signal.

In another method embodiment of the present invention, illustrated inFIG. 3, an estimated variance of the signal rate of change iscalculated. For example, for engine compressor fans having speed signalNfan, it is preferable to calculate the estimated variance of the speedsignal rate of change d(Nfan)/dt, using the equation:

Variance[d(Nfan)/dt]=Filtered [(d(Nfan)/dt)² ]−(Filtered [d(Nfan)/dt])²

In this algorithm, the approximate value of the expectation operation(E), which is the estimated short term average signal x, is obtained bya filter.

FIG. 3 illustrates a flowchart of this method embodiment of the presentinvention, for estimation of the short-term variance of a signal rate ofchange. This flowchart shows variance detection as actually implementedin AS900 turbofan engine manufactured by Honeywell International, Inc.Thus, it shows several preliminary testing steps 300-304. In step 300, asensor is read to obtain the tested signal. In step 302, the sensor istested. In step 304, it is determined whether the reading is valid and,if not, step 370 is executed. If valid, in step 306, the rate of changeof the signal is calculated. In step 308, the tested input signal issquared. In step 310, an estimate average of the squared input signal isobtained via filtering, generating an estimate of the average of x² overthe short term. In step 320, an estimate average of the input signal isobtained via filtering. It is then squared, generating a squaredestimate of the average of x over the short term, for use in step 330.In step 330, an estimate of the short term variance is calculated usingthe equation for variance: Var[x]=E[x²]−E²[x], where E is theexpectation operator, or average.

In step 340, the estimated variance value is compared with a predefinedvariance limit and latching counter of the rate test. In step 350, it istested whether the estimated variance exceeds the predefined limit for agiven amount of time. If not, the test is over in step 360. If theestimated variance exceeds the predefined limit for a given amount oftime, in step 370, the signal is deemed to be inaccurate and invalidbecause the variance is too high to be that of a real signal.

FIG. 4 illustrates a block diagram of a signal variance detection logicwhich implements the method embodiment of the present invention, usedfor estimation of the short-term variance of a signal rate of change. Inelement 400, the rate of change (time derivative) of an input signal iscalculated. In a multiplier 402, the tested input signal rate of changeis squared. In element 410, an estimate average of the squared inputsignal rate of change is obtained via filtering. In element 420, anestimate average of the input signal rate of change is obtained viafiltering. In multiplier 425, this signal is squared. In element 430, anestimate variance is calculated by subtraction of the two estimatedsignals obtained from elements 410 and 425. In element 440, thecalculated estimated variance value is compared with a predefinedvariance limit of the rate test. In latching counter (timer) 450, it istested whether the estimated variance exceeds the predefined variancelimit for a predefined amount of time. If the estimated variance exceedsthe predefined limit for a given amount of time, the signal is deemed tobe inaccurate and invalid because the variance is too high to be that ofa real signal.

Similar approaches can be used for other gas turbine signals, estimatingeither the variance of the signal or the variance of the rate of changeof the signal, and then comparing the estimated variance with apredefined limit to detect signal failure.

The preferred embodiments of the present invention of may be embeddedeither into the gas turbine ECU software application or in the ECUhardware circuitry.

An estimate of the average short term variance of an input signal orrate of change is preferably obtained via analog or digital filters. Thepreferred system embodiments of the present invention preferably usefilters which are simple first order lags, but higher order filters orother signal averaging modules may be used as well. Two digital filtermethods may be used in the present invention. The first method includescalculation of a rolling average. The second method includes calculationof a filtered value of the input stream.

The method of calculating a rolling average of the z most current signalinput reading drops the oldest reading from the average each time a newreading is available. The calculation is performed according to theequation:

y(n)=[x(n)+x(n−1)+x(n−2)+ . . . +x(n−(z−1))]/(z)

where: y(n) is the current estimate of the average at iteration n, x(n)is the current value of the input to the filter, x(n−1) is the previousvalue of the input to the filter, x(n−2) is the 2 nd last value of theinput to the filter, and x(n−(z−1)) is the (z−1)th last value of theinput to the filter.

To calculate a filtered value of the input stream, two types of filterscan be used in the digital embodiments: finite impulse response filtersand infinite impulse response filters. Finite impulse response (FIR)filters calculate a weighted rolling average of the z most currentreadings; this is similar to a rolling average but with weights. Theweights allow tailoring of the frequency response of the averaging,according to the equation:

y(n)=[w1x(n)+w2x(n−1)+w3x(n−2)+ . . . +wz x(n−(z−1))]/(w1 +w2+w3. . .+wz)

where: y(n) is the current estimate of the average at iteration n, x(n)is the current value of the input to the filter, x(n−1) is the previousvalue of the input to the filter, x(n−2) is the 2 nd last value of theinput to the filter, x(n −(z−1)) is the (z−1)th last value of the inputto the filter, and w1-wz are weighting coefficients used to tailor thefrequency or time response characteristics of the filter.

Infinite impulse response (IIR) filters are digital embodiments ofstandard analog filters. IIR filters weight recent input data morestrongly than older data. As a datum become older and older, its weightdwindles to essentially zero.

y(n)=a1y(n−1)+a2y(n−2)+ . . . +az y(n−z)+b1x(n)+b2x(n−1)+ . . . bwx(n−(w−1))

where: y(n) is the current estimate of the average at iteration n,y(n−1) is the last value of the estimate of the average, y(n−z) is the(z−1)th last value of the estimate of the average, x(n) is the currentvalue of the input to the filter, x(n−1) is the last value of the inputto the filter, x(n−(w−1)) is the (w−1)th last value of the input to thefilter, a1-az and b1-bw are weighting coefficients used to tailor thefrequency or time response characteristics of the filter. The weightingcoefficients sum to 1.0.

Analog filter circuitry embodiments of the invention will typically usetraditional analog filters that function similarly to digital IIRfilters.

The preferred embodiments of the present invention were implemented inthe fan speed signal (N1) derived from a suitable fan speed transduceror sensor on AS900, and utilize a simple digital IIR filter forestimating the short term averages, according to the equation:

y(n)=0.818 y(n−1)+0.091 x(n)+0.091 x(n−1)

where: y(n) is the current estimate of the average, y(n−1) is the lastvalue of the estimate of the average, x(n) is the current value of theinput to the filter, x(n−1) is the last value of the input to thefilter, and x and y are calculated, depending on the sample rate of N1speed, at a 50 ms or 100 ms rate. This results in a shift in frequencyresponse of the averager/filter as the sampling rate changes, butproduces the desired result in the AS900 N1 speed case.

Preferably, the latching counter (timer) 250, 450 of the presentinvention utilizes a unique algorithm that times out faster if the inputconstantly equals one, as shown in FIG. 5. The timer times out at aslower rate when the input equals one “most of the time”. Thus, the rateis dependent on the proportion of time the input equals one.

The preferred embodiments of the present invention may be used in twoways. Firstly, they may be used on-line to detect and accommodatefailures as they occur, in order to insure continued safe engineoperation, as would be the case with a speed signal failure or blade outevent. Secondly, they may be used off-line to predict future failuresand allow for maintenance before a future failure occurs, as might bethe case with typical gas turbine hot section temperature probes signalsthat are averaged electrically in the probe assembly. There, althoughoperation is not initially affected as the individual probes fail,variance increases with each probe failure. Moreover, the preferredembodiments of the present invention may be used to determine thevalidity of sensor signals for any electronic control sensor, such asautomotive oxygen content sensors, chemical factory mixturetemperature/pressure sensors, etc.

It should be understood, of course, that the foregoing relates topreferred embodiments of the invention and that modifications may bemade without departing from the spirit and scope of the invention as setforth in the following claims.

We claim:
 1. A signal fault detection method useable in electricalcontrol sensors for shaft speed signal frequency change rate tests,detecting intermittent or “in-range” failures of the signal, comprising:means for measuring frequency of a shaft speed signal; means forestimating a short-term variance of the measured signal using theequation: Var[x]=E[x−E(x)]²=E[x²]−E²[x], where x is the measured signal,E(x) is the expected value of x, E[x]is the expected value of x²,calculated by estimating the average of x² over a predefined short term,and E²[x] is the squared value of E[x], where E[x] is calculated byestimating the average of the measured signal x over the predefinedshort term; means for estimating the short-term varianceVar[x]=E[x²]−E²[x] by employing the following algorithm: Var[x]=Filtered[(x)²]−(Filtered [x])²; means for comparing the estimated variance witha predefined variance limit for a predefined amount of time; and meansfor deeming the measured signal at least one of faulted and invalid, ifthe estimated variance exceeds the predefined variance limit for thepredefined amount of time.
 2. The system according to claim 1, whereinthe means for comparing the estimated variance with a predefinedvariance limit for a predefined amount of time includes a latchingcounter.
 3. The system according to claim 1, wherein the means forestimating a short-term variance of the measured signal by employing anaveraging filter to perform the expectation operation, where theaveraging filter includes a plurality of filters performing averagingfunction in the calculation of E[x²] and E²[x].
 4. The system accordingto claim 3, wherein the filters selected from a group comprising analogfilters, digital IIR filters, digital FIR filters, and rolling averagefilters.
 5. The system according to claim 1, wherein the system beingimplemented in a software program includes a set of computer-executableprogram instructions.
 6. The system according to claim 1, wherein thesystem being implemented is in a hardware circuitry.
 7. A method useablein electrical control sensors for shaft speed signal frequency changerate tests, detecting intermittent or “in-range” failures, comprisingthe following steps: (a) measuring frequency of a shaft speed signal;(b) estimating a short-term variance of the measured signal using theequation: Var[x]=E[x²]−E²[x], where E[x²] is ] is an estimated averageof the squared measured signal over a predefined short term, and E²[x]is a squared estimated average of the measured signal over thepredefined short term; (c) comparing the estimated short-term variancewith a predefined short-term variance limit for a predefined amount oftime; and (d) if the estimated short-term variance exceeds thepredefined variance limit for the predefined amount of time, deeming themeasured signal invalid.
 8. The method according to claim 7, wherein thestep for comparing the estimated variance with a predefined variancelimit for a predefined amount of time uses a latching counter.
 9. Themethod according to claim 7, wherein the step for estimating ashort-term variance of the measured signal using a plurality of filtersperforms averaging function.
 10. The method according to claim 9,wherein the filters selected from a group comprising analog filters,digital FIR filters, digital FIR filters, and rolling average filters.11. The method according to claim 7, wherein the method beingimplemented in a software program includes a set of computer-executableprogram instructions executed within a gas turbine engine controlsystem.
 12. The method according to claim 7, wherein the method beingimplemented is in a hardware circuitry.